Triple

T5694792
Position Surface form Disambiguated ID Type / Status
Subject John Tortorella E125511 entity
Predicate givenName P17 FINISHED
Object John
John Tortorella is an American professional ice hockey coach best known for his fiery personality and successful NHL coaching career, including a Stanley Cup win with the Tampa Bay Lightning.
E545348 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: John | Statement: [John Tortorella, givenName, John]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John
Context triple: [John Tortorella, givenName, John]
  • A. John
    John is the given name of John Arbuthnot Fisher, a prominent British admiral and naval reformer of the late 19th and early 20th centuries.
  • B. John
    John is the given name of the American composer John Luther Adams, known for his works inspired by nature and environmental themes.
  • C. John
    John is the given name of John Adams, the prominent American minimalist and post-minimalist composer known for works like "Nixon in China" and "Short Ride in a Fast Machine."
  • D. John
    John is the given first name of American character actor and comedian Rags Ragland.
  • E. John
    John is the given name of actor John Cho, a Korean American performer known for roles in the "Harold & Kumar" films and the "Star Trek" reboot series.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: John
Triple: [John Tortorella, givenName, John]
Generated description
John Tortorella is an American professional ice hockey coach best known for his fiery personality and successful NHL coaching career, including a Stanley Cup win with the Tampa Bay Lightning.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: John
Target entity description: John Tortorella is an American professional ice hockey coach best known for his fiery personality and successful NHL coaching career, including a Stanley Cup win with the Tampa Bay Lightning.
  • A. John
    John is the given first name of Johnny Bucyk, a Hall of Fame Canadian ice hockey player best known for his long career with the Boston Bruins.
  • B. John
    John is the first name of Jack Ramsay, the renowned American basketball coach and Hall of Famer.
  • C. John
    John is the first name of J. Michael Luttig, a prominent American conservative jurist and former federal appellate judge.
  • D. John
    John is the first name of former NFL quarterback Joey Harrington, who played primarily for the Detroit Lions in the early 2000s.
  • E. John
    John is the given name of John Madden, the famed American football coach, broadcaster, and namesake of the Madden NFL video game series.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69c0082bb19c8190823a4facd3cba79b completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02409e70081909e47f2bd4a50fa12 completed March 22, 2026, 5:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c07ddd0f248190a796055212284542 completed March 22, 2026, 11:40 p.m.
NEDg Description generation batch_69c08a536ecc8190a4a0391e28076d44 completed March 23, 2026, 12:33 a.m.
NED2 Entity disambiguation (via description) batch_69c08ad660688190b5d3563ac2a9d0d9 completed March 23, 2026, 12:35 a.m.
Created at: March 22, 2026, 3:45 p.m.